40 research outputs found
Survey on Identification of Hacker by Trapping Mechanism
No full textAdvanced persistence threat APT attack is to steal data rather than to cause damage to the network or organization. It is one of the initial phases in successful hacking of a system. Here, user's behaviour is analysed based on previous behaviour such as posted data, time of posting, IP address and location of usage of social network. This system includes two processes. The Social network accounts are analysed, tracked and then detected. If the hacker attacks the original user's account, then the system allows the attacker to proceed further until our system captures all the important information about the attacker by directing the hacker to the fake website. The system generates Honeywords based on the user information provided and the original password is converted into another format and stored along with the honeywords. Attacker who knows the E mail account of original user can easily reset the password of the cloud server. When the attacker tries to login into the purchase portal, he she is tracked and allowed to do purchase. Server identifies the attacker and sends an alert message to the owner and blocks the attacker from doing transaction from his original account. C. Ramprasath | J. Varun | Ms S. SriHeera "Survey on Identification of Hacker by Trapping Mechanism" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: https://www.ijtsrd.com/papers/ijtsrd10789.pd
Design and Analysis of Single Switch Double Enhanced Boost Converter for PV Applications
No full textThis paper presents a systematic and analytical investigation of the non-isolated Single Switch Double Enhanced Boost Converter topology. In simple words combination of a DEC (Double Enhanced Circuit) With an ordinary boost converter. The proposed converter implements the output voltage increasing in geometric progression but with a simpler structure. There is one switch S, n inductors, (n + 2) capacitors, and (2n + 1) diodes in each circuit of the additional series. They also effectively enhance the voltage transfer gain in the power law. Steady-state equations were derived to examine the behaviour of the proposed converter. The proposed converter was designed for 100 W and simulated in MATLAB/Simulink, the simulation results demonstrate its effectiveness in terms of improved efficiency, reduced voltage stress, and enhanced power delivery to the load
Beneficial role of silibinin in monitoring the cadmium induced hepatotoxicity in Albino Wistar rats
No full textCadmium (Cd), an environmental toxic pollutant affects many organs in human beings specially the liver and kidney. In this study, Cd (3 mg/kg body weight (b.w.)) was subcutaneously administered to rats for 3 weeks, which shows significantly (
Protective role of silibinin in cadmium induced changes of acetylcholinesterase, ATPases and oxidative stress in brain of albino wistar rats
No full textCadmium (Cd) a highly toxic metal is considered to be a multitarget toxicant, principally its accumulates in the liver, kidney and hardly get into the brain parenchyma by the brain-barrier system. In this study, Cd (3 mg/kg body weight (b. w.)) was subcutaneously administered to rats for 3 weeks, which shows significantly (
Topics in statistical finance
No full textThis thesis is divided into three parts. The first part investigates the presence of long term dependence in stock price data via a permutation test based on the correlation structure of the underlying stock prices. These tests reveal the short term nature of stock price dependence structure. The second part extends
Ramprasath and Singh(2007)'s `statistical options' to define a group of American type options based on robust estimators of location. The payoff functions of these path dependent options are based on a new set of stochastic processes which are defined using various robust estimators of location. The asymptotic distributional behavior of these new processes is ascertained which in turn is used in pricing
the options. Markov Chain Monte Carlo (MCMC) methods were used to compute the prices of the statistical options. The third part explores a stock price model parameter estimation problem and interprets a growth rate parameter.Ph.D.Includes bibliographical references (p. 81-83)
Partial Purification of Extracellular Amylase From Halotolerant Actinomycetes Streptomyces brasiliensis MML2028
No full textAmylase is considered as an industrially important enzyme as it occupies the most important function in the food, paper, and pharmaceutical industries. The present study is concerned with the optimization, production and partial purification of halotolerant amylase from newly isolated Streptomyces brasiliensis MML2028, from Kelambakkam salt pan, Tamil Nadu, India. The primary screening was carried out by well diffusion assay to find the zone of lysis. The assay was observed for each media optimization by measuring the release of reducing sugar (RS) by the 3,5 dinitro salicylic acid (DNS) method and expressed in the international unit (UI). Ammonium sulphate precipitation was used to partially purify the enzyme and then lyophilized. SDS-PAGE was performed to identify the molecular weight. The production medium was optimized with 1% of the starch substrate, 3% of NaCl at 24˚C and pH 9, and incubation of 9 days. The total activity of the partially purified α-amylase was observed to be 1806.9U/mL. The partially purified enzyme was more active with 3% NaCl, pH 8, and 24˚C which is known to be a halotolerant alkaline α-amylase. The enzyme showed tolerance towards magnesium, manganese ions, Triton x-100, and urea. De-inking of α-amylase showed good results proving that the enzyme activity is more efficient. Hence, the alkaliphilic amylase from Halotolerant actinomycetes S. Brasiliensis MML2028 could be a better microbial source that can be used in many industries, especially in paper and textiles
White shark optimizer with optimal deep learning based effective unmanned aerial vehicles communication and scene classification.
No full textUnmanned aerial vehicles (UAVs) become a promising enabler for the next generation of wireless networks with the tremendous growth in electronics and communications. The application of UAV communications comprises messages relying on coverage extension for transmission networks after disasters, Internet of Things (IoT) devices, and dispatching distress messages from the device positioned within the coverage hole to the emergency centre. But there are some problems in enhancing UAV clustering and scene classification using deep learning approaches for enhancing performance. This article presents a new White Shark Optimizer with Optimal Deep Learning based Effective Unmanned Aerial Vehicles Communication and Scene Classification (WSOODL-UAVCSC) technique. UAV clustering and scene categorization present many deep learning challenges in disaster management: scene understanding complexity, data variability and abundance, visual data feature extraction, nonlinear and high-dimensional data, adaptability and generalization, real-time decision making, UAV clustering optimization, sparse and incomplete data. the need to handle complex, high-dimensional data, adapt to changing environments, and make quick, correct decisions in critical situations drives deep learning in UAV clustering and scene categorization. The purpose of the WSOODL-UAVCSC technique is to cluster the UAVs for effective communication and scene classification. The WSO algorithm is utilized for the optimization of the UAV clustering process and enables to accomplish effective communication and interaction in the network. With dynamic adjustment of the clustering, the WSO algorithm improves the performance and robustness of the UAV system. For the scene classification process, the WSOODL-UAVCSC technique involves capsule network (CapsNet) feature extraction, marine predators algorithm (MPA) based hyperparameter tuning, and echo state network (ESN) classification. A wide-ranging simulation analysis was conducted to validate the enriched performance of the WSOODL-UAVCSC approach. Extensive result analysis pointed out the enhanced performance of the WSOODL-UAVCSC method over other existing techniques. The WSOODL-UAVCSC method achieved an accuracy of 99.12%, precision of 97.45%, recall of 98.90%, and F1-score of 98.10% when compared to other existing techniques
Limb salvage after delayed arterial repair in compound Grade III C fracture humerus: a case report
No full text<p>A combination of brachial artery injury and fracture shaft of humerus is a rare phenomenon. There is a general apprehension regarding survival of a limb after vascular injury. Only few studies exist in literature that discuss about the survival of such limbs. Our case is a 56 years old female patient who presented three hours after sustaining injury in the form of fracture shaft of humerus and complete transection of brachial artery distal to the origin of profunda brachii. Even though Doppler USG done initially revealed flow in the vessels distal to the injury, a CT Angiogram done later revealed cutting of the brachial artery. This prompted us to perform brachial artery exploration and repair. post operatively, digital subtraction angiography showed absence of flow in the brachial artery but limb survived due to extensive collateral circulation. Even after the golden period of vascular repair has lapsed, arterial repair is recommended if there is no evidence of gangrene. This should be supplemented with adequate systemic anticoagulants and/or fasciotomy.</p></jats:p
Assessment of induction of physiological cardiac hypertrophy.
No full text<p>A. Representative photographs of the hypertrophied and control heart B. Heart weight/ body weight ratio. C. Representative histopathology images of hypertrophied and control cardiomyocytes. D. Cell profiler analysis of cell length and area of the cardiomyocytes. The values represent the mean±SD of six animals. Asterisk represents the statistical significance by Mann-Whitney U test at p-value < 0.005</p
